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Deep reinforcement learning hands-on : apply modern RL methods to practical problems of chatbots, robotics, discrete optimization web automation, and more / 2nd ed

Deep reinforcement learning hands-on : apply modern RL methods to practical problems of chatbots, robotics, discrete optimization web automation, and more / 2nd ed (Loan 3 times)

Material type
단행본
Personal Author
Lapan, Maxim.
Title Statement
Deep reinforcement learning hands-on : apply modern RL methods to practical problems of chatbots, robotics, discrete optimization web automation, and more / Maxim Lapan.
판사항
2nd ed.
Publication, Distribution, etc
Birmingham :   Packt,   c2020.  
Physical Medium
xix, 798 p. : ill. ; 24 cm.
ISBN
9781838826994
General Note
Includes index.  
"2nd ed. - includes multi-agent methods and advanced exploration techniques"--cover.  
Subject Added Entry-Topical Term
Reinforcement learning. Machine learning.
000 00000cam u2200205 a 4500
001 000046032557
005 20200615113423
008 200615s2020 enka 001 0 eng d
020 ▼a 9781838826994
035 ▼a (KERIS)BIB000015598495
040 ▼a 211009 ▼c 211009 ▼d 244019 ▼d 211009
082 0 4 ▼a 006.31 ▼2 23
084 ▼a 006.31 ▼2 DDCK
090 ▼a 006.31 ▼b L299d2
100 1 ▼a Lapan, Maxim.
245 1 0 ▼a Deep reinforcement learning hands-on : ▼b apply modern RL methods to practical problems of chatbots, robotics, discrete optimization web automation, and more / ▼c Maxim Lapan.
250 ▼a 2nd ed.
260 ▼a Birmingham : ▼b Packt, ▼c c2020.
300 ▼a xix, 798 p. : ▼b ill. ; ▼c 24 cm.
500 ▼a Includes index.
500 ▼a "2nd ed. - includes multi-agent methods and advanced exploration techniques"--cover.
650 0 ▼a Reinforcement learning.
650 0 ▼a Machine learning.
945 ▼a KLPA

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Science & Engineering Library/Sci-Info(Stacks2)/ Call Number 006.31 L299d2 Accession No. 121253484 Availability In loan Due Date 2021-07-16 Make a Reservation Available for Reserve R Service M

Contents information

Table of Contents

Table of Contents

What Is Reinforcement Learning?
OpenAI Gym
Deep Learning with PyTorch
The Cross-Entropy Method
Tabular Learning and the Bellman Equation
Deep Q-Networks
Higher-Level RL libraries
DQN Extensions
Ways to Speed up RL
Stocks Trading Using RL
Policy Gradients - an Alternative
The Actor-Critic Method
Asynchronous Advantage Actor-Critic
Training Chatbots with RL
The TextWorld environment
Web Navigation
Continuous Action Space
RL in Robotics
Trust Regions - PPO, TRPO, ACKTR, and SAC
Black-Box Optimization in RL
Advanced exploration
Beyond Model-Free - Imagination
AlphaGo Zero
RL in Discrete Optimisation
Multi-agent RL

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